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Solution-processed memristors: performance and reliability

Nature Reviews Materials (2024)Cite this article

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Abstract

Memristive devices are gaining importance in the semiconductor industry for applications in information storage, artificial intelligence cryptography and telecommunication. Memristive devices fabricated by solution-processing methods can be integrated into a wide variety of large-area substrates, which has motivated their use in applications requiring flexible, stretchable, transparent and biocompatible devices. Several studies on solution-processed memristors have claimed excellent electrical performance; however, in many cases such claims are based on scarce measurements conducted on only one device, using unreliable testing protocols or using device structures that are too large for the target applications. Understanding the reliability of a memristive structure is important to avoid hyped expectations, attract potential investments in such technology, and realistically understand its potential impact on society and on the market. In this Perspective, we analyse which solution-processed memristors have so far exhibited the highest and most reliable electronic performance, irrespective of the type of material used and the application targeted. For that group of memristors, we also discuss the switching mechanism and potential applications, as well as possible improvements in terms of device technology. We describe the outlook of this field with aims of increasing the impact and technology readiness of solution-processed memristors.

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Fig. 1: General overview of the structure, electrical behaviour and application of memristors.
Fig. 2: Figures-of-merit of solution-processed memristors.
Fig. 3: Fabrication methods and switching mechanism assessment in best-performance solution-processed memristors.
Fig. 4: Device integration and consistency with intended applications for solution-processed memristors.

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Acknowledgements

The authors thank the Baseline funding scheme of the King Abdullah University of Science and Technology for support, as well as F. Aguirre from the company Intrinsic for discussions and literature about memristive neural networks. M.L. acknowledges the platform Web of Talents (https://weboftalents.com) for support in the recruitment of talented students and postdocs.

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  1. Materials Science and Engineering, Physical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia

    Sebastian Pazos, Xiangming Xu, Tianchao Guo, Kaichen Zhu, Husam N. Alshareef & Mario Lanza

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  1. Sebastian Pazos
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  2. Xiangming Xu
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  3. Tianchao Guo
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  4. Kaichen Zhu
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  5. Husam N. Alshareef
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  6. Mario Lanza
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Contributions

M.L. conceptualized the article. S.P., X.X., T.G. and K.Z. did the literature search. S.P., X.X., T.G. and M.L. wrote the manuscript. H.N.A. contributed discussions on technical aspects of the fabrication process of the devices and revised the manuscript. All authors discussed the structure and revised the final version of the text.

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Correspondence to Mario Lanza.

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Pazos, S., Xu, X., Guo, T. et al. Solution-processed memristors: performance and reliability. Nat Rev Mater (2024). https://doi.org/10.1038/s41578-024-00661-6

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